The multigrid POTFIT (MGPF) method: grid representations of potentials for quantum dynamics of large systems
In this article, a new method, multigrid POTFIT (MGPF), is presented. MGPF is a grid-based algorithm which transforms a general potential energy surface into product form, that is, a sum of products of one-dimensional functions. This form is necessary to profit from the computationally advantageous...
Gespeichert in:
| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
3 January 2013
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| In: |
The journal of chemical physics
Year: 2013, Jahrgang: 138, Heft: 1, Pages: 1-16 |
| ISSN: | 1089-7690 |
| DOI: | 10.1063/1.4773021 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1063/1.4773021 Verlag, lizenzpflichtig, Volltext: https://aip.scitation.org/doi/10.1063/1.4773021 
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| Verfasserangaben: | Daniel Peláez and Hans-Dieter Meyer |
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| 520 | |a In this article, a new method, multigrid POTFIT (MGPF), is presented. MGPF is a grid-based algorithm which transforms a general potential energy surface into product form, that is, a sum of products of one-dimensional functions. This form is necessary to profit from the computationally advantageous multiconfiguration time-dependent Hartree method for quantum dynamics. MGPF circumvents the dimensionality related issues present in POTFIT [A. Jäckle and H.-D. Meyer, J. Chem. Phys. 104, 7974 (1996) https://doi.org/10.1063/1.471513.], allowing quantum dynamical studies of systems up to about 12 dimensions. MGPF requires the definition of a fine grid and a coarse grid, the latter being a subset of the former. The MGPF approximation relies on a series of underlying POTFIT calculations on grids which are smaller than the fine one and larger than or equal to the coarse one. This aspect makes MGPF a bit less accurate than POTFIT but orders of magnitude faster and orders of magnitude less memory demanding than POTFIT. Moreover, like POTFIT, MGPF is variational and provides an efficient error control. | ||
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